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From Pat Ferrel <...@occamsmachete.com>
Subject Re: Problem using SNAPSHOT kmeans
Date Tue, 05 Jun 2012 18:48:28 GMT
Using seqdumper on the TFIDF vectors, that vector is indeed in the list
Key: https://farfetchers.com/category/collections/source/brice-berard:
Value: https://farfetchers.com/category/collections/source/brice-berard:{

Looking in the seqfiles we find the document in part-00005 of 10 in no 
particular part of the file.
Key: https://farfetchers.com/category/collections/source/brice-berard:
Value: ::Title::
Brice Berard | FarFetchers.com
Blog Posts

On the chance that this originates in seq2sparse I'll try changing 
options until the vector looks different. and try clustering again.

On 6/5/12 10:43 AM, Pat Ferrel wrote:
> I'm not completely sure what I'm looking at but...
>
> In iterateSeq on iteration #1  of processing vectors/tfidf-vectors it 
> reads
> vector = 
> "https://farfetchers.com/category/collections/source/brice-berard:{"
>
> it's a named vector where the  url is the name, the value is "{", 
> which looks wrong and when that is classified to get a probability it 
> gets
>
> probabilities = 
> "{0:NaN,1:NaN,2:NaN,3:NaN,4:NaN,5:NaN,6:NaN,7:NaN,8:NaN,9:NaN,10:NaN,11:NaN,12:NaN,13:NaN,14:NaN,15:NaN,16:NaN,17:NaN,18:NaN,19:NaN}"
>
> That causes the probabilities.maxValueIndex() = -1 and everything dies.
>
> vector looks wrong, doesn't it? Truncated?
>
> I went back to try the same on mahout 0.6 but iterateSeq does not get 
> called though I used -xm sequential on both runs. I can't see 
> kmeans-clusters/clusters-0 being created on mahout 0.6 either. Is that 
> part of the refactoring?
>
> On 6/4/12 3:07 PM, Pat Ferrel wrote:
>> Some things to try:
>> - Have you verified the contents of your input vectors actually have 
>> data in them?
>> * YES, from the other email you know that the data works fine in 0.6
>> - Can you run the cluster dumper on the b3/kmeans-clusters/clusters-0 
>> contents?
>> * YES, It is attached from trunk's clusterdump after the failure of 
>> kmeans, of course. A simple data set fortunately.
>> - Is it possible to run the sequential version (-xm sequential)? If 
>> it is you could run it in a debugger to gain more insight.
>> * YES, will report back.
>>
>> On 6/4/12 2:19 PM, Jeff Eastman wrote:
>>> It looks like the probabilities vector returned by 
>>> AbstractClusteringPolicy.classify() has no non-zero elements. In 
>>> this case, AbstractClusteringPolicy.select()'s call to 
>>> AbstractVector.maxValueIndex() is returning -1 and that is causing 
>>> the exception.
>>>
>>> How could this happen? I'm not exactly sure, but consider that the 
>>> probabilities vector is calculated in 
>>> AbstractClusteringPolicy.classify() by calling 
>>> DistanceMeasureCluster.pdf() on each of the prior clusters in 
>>> b3/kmeans-clusters/clusters-0. With a CosineDistanceMeasure I don't 
>>> see how this could ever return zero. Certainly, some of your vectors 
>>> will match the prior cluster centers exactly (they were sampled from 
>>> the input) and those values would return pdf==1. Even if the cosine 
>>> distance was 1 the pdf would be 0.5.
>>>
>>> Some things to try:
>>> - Have you verified the contents of your input vectors actually have 
>>> data in them?
>>> - Can you run the cluster dumper on the 
>>> b3/kmeans-clusters/clusters-0 contents?
>>> - Is it possible to run the sequential version (-xm sequential)? If 
>>> it is you could run it in a debugger to gain more insight.
>>>
>>> Jeff
>>>
>>> On 6/4/12 12:05 PM, Pat Ferrel wrote:
>>>> Using the CLI to kmeans from several trunk versions I get an error 
>>>> I don't understand.  When the job died the 
>>>> b3/canopy-centroids/clusters-0-final contained the random-seeds 
>>>> file generated by the kmeans driver and the 
>>>> b3/kmeans-clusters/clusters-0 had several part files but 
>>>> b3/kmeans-clusters/clusters-1 was empty. When I look through the 
>>>> code from the trace it doesn't make much sense.
>>>>
>>>> Command line:
>>>> mahout kmeans
>>>>   -i b3/vectors/tfidf-vectors/
>>>>   -k 20
>>>>   -c b3/canopy-centroids/clusters-0-final
>>>>   -cl
>>>>   -o b3/kmeans-clusters
>>>>   -ow
>>>>   -cd 0.01
>>>>   -x 30
>>>>   -dm org.apache.mahout.common.distance.CosineDistanceMeasure
>>>>
>>>> Error:
>>>> 12/06/04 07:55:03 INFO common.AbstractJob: Command line arguments: 
>>>> {--clustering=null, 
>>>> --clusters=[b3/canopy-centroids/clusters-0-final], 
>>>> --convergenceDelta=[0.01], 
>>>> --distanceMeasure=[org.apache.mahout.common.distance.CosineDistanceMeasure],

>>>> --endPhase=[2147483647], --input=[b3/vectors/tfidf-vectors/], 
>>>> --maxIter=[30], --method=[mapreduce], --numClusters=[20], 
>>>> --output=[b3/kmeans-clusters], --overwrite=null, --startPhase=[0], 
>>>> --tempDir=[temp]}
>>>> 2012-06-04 07:55:03.752 java[67308:1903] Unable to load realm info 
>>>> from SCDynamicStore
>>>> 12/06/04 07:55:03 INFO common.HadoopUtil: Deleting 
>>>> b3/canopy-centroids/clusters-0-final
>>>> 12/06/04 07:55:04 WARN util.NativeCodeLoader: Unable to load 
>>>> native-hadoop library for your platform... using builtin-java 
>>>> classes where applicable
>>>> 12/06/04 07:55:04 INFO compress.CodecPool: Got brand-new compressor
>>>> 12/06/04 07:55:04 INFO kmeans.RandomSeedGenerator: Wrote 20 vectors 
>>>> to b3/canopy-centroids/clusters-0-final/part-randomSeed
>>>> 12/06/04 07:55:04 INFO kmeans.KMeansDriver: Input: 
>>>> b3/vectors/tfidf-vectors Clusters In: 
>>>> b3/canopy-centroids/clusters-0-final/part-randomSeed Out: 
>>>> b3/kmeans-clusters Distance: 
>>>> org.apache.mahout.common.distance.CosineDistanceMeasure
>>>> 12/06/04 07:55:04 INFO kmeans.KMeansDriver: convergence: 0.01 max 
>>>> Iterations: 30 num Reduce Tasks: 
>>>> org.apache.mahout.math.VectorWritable Input Vectors: {}
>>>> 12/06/04 07:55:04 INFO compress.CodecPool: Got brand-new decompressor
>>>> Cluster Iterator running iteration 1 over priorPath: 
>>>> b3/kmeans-clusters/clusters-0
>>>> 12/06/04 07:55:05 INFO input.FileInputFormat: Total input paths to 
>>>> process : 1
>>>> 12/06/04 07:55:05 INFO mapred.JobClient: Running job: job_local_0001
>>>> 12/06/04 07:55:06 INFO mapred.MapTask: io.sort.mb = 100
>>>> 12/06/04 07:55:08 INFO mapred.MapTask: data buffer = 79691776/99614720
>>>> 12/06/04 07:55:08 INFO mapred.MapTask: record buffer = 262144/327680
>>>> 12/06/04 07:55:08 INFO mapred.JobClient:  map 0% reduce 0%
>>>> 12/06/04 07:55:09 WARN mapred.LocalJobRunner: job_local_0001
>>>> org.apache.mahout.math.IndexException: Index -1 is outside 
>>>> allowable range of [0,20)
>>>>     at 
>>>> org.apache.mahout.math.AbstractVector.set(AbstractVector.java:439)
>>>>     at 
>>>> org.apache.mahout.clustering.iterator.AbstractClusteringPolicy.select(AbstractClusteringPolicy.java:44)
>>>>     at 
>>>> org.apache.mahout.clustering.iterator.CIMapper.map(CIMapper.java:52)
>>>>     at 
>>>> org.apache.mahout.clustering.iterator.CIMapper.map(CIMapper.java:18)
>>>>     at org.apache.hadoop.mapreduce.Mapper.run(Mapper.java:144)
>>>>     at org.apache.hadoop.mapred.MapTask.runNewMapper(MapTask.java:764)
>>>>     at org.apache.hadoop.mapred.MapTask.run(MapTask.java:370)
>>>>     at 
>>>> org.apache.hadoop.mapred.LocalJobRunner$Job.run(LocalJobRunner.java:212)

>>>>
>>>> 12/06/04 07:55:09 INFO mapred.JobClient: Job complete: job_local_0001
>>>> 12/06/04 07:55:09 INFO mapred.JobClient: Counters: 0
>>>> Exception in thread "main" java.lang.InterruptedException: Cluster 
>>>> Iteration 1 failed processing b3/kmeans-clusters/clusters-1
>>>>     at 
>>>> org.apache.mahout.clustering.iterator.ClusterIterator.iterateMR(ClusterIterator.java:186)
>>>>     at 
>>>> org.apache.mahout.clustering.kmeans.KMeansDriver.buildClusters(KMeansDriver.java:229)
>>>>     at 
>>>> org.apache.mahout.clustering.kmeans.KMeansDriver.run(KMeansDriver.java:149)
>>>>     at 
>>>> org.apache.mahout.clustering.kmeans.KMeansDriver.run(KMeansDriver.java:108)
>>>>     at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:65)
>>>>     at 
>>>> org.apache.mahout.clustering.kmeans.KMeansDriver.main(KMeansDriver.java:49)
>>>>     at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
>>>>     at 
>>>> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39)
>>>>     at 
>>>> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25)
>>>>     at java.lang.reflect.Method.invoke(Method.java:597)
>>>>     at 
>>>> org.apache.hadoop.util.ProgramDriver$ProgramDescription.invoke(ProgramDriver.java:68)
>>>>     at 
>>>> org.apache.hadoop.util.ProgramDriver.driver(ProgramDriver.java:139)
>>>>     at 
>>>> org.apache.mahout.driver.MahoutDriver.main(MahoutDriver.java:195)
>>>>
>>>>
>>>>
>>>>
>>>>
>>>

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